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AGN Reverberation Mapping with LITMUS: Fundamental Limits on lag Recovery Rates
Authors:
Hugh McDougall,
Tamara M. Davis,
Benjamin J. S. Pope,
Paul Martini,
Zhefu Yu,
Chris Lidman,
Geraint F. Lewis
Abstract:
Reverberation mapping of active galactic nuclei provides one of the most direct probes of the geometry and kinematics of the broad-line region by measuring time delays between continuum and line variability. Modern RM surveys frequently suffer difficulties with lag measurements due to poor signal to noise and aliasing, whereby multimodal lag posterior distributions arise due to seasonal gaps in ou…
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Reverberation mapping of active galactic nuclei provides one of the most direct probes of the geometry and kinematics of the broad-line region by measuring time delays between continuum and line variability. Modern RM surveys frequently suffer difficulties with lag measurements due to poor signal to noise and aliasing, whereby multimodal lag posterior distributions arise due to seasonal gaps in our data. These challenge the reliability of commonly used fitting tools such as JAVELIN, which can return a high rate of false positives. We implement a new lag measurement package, LITMUS, and introduce a new framework that uses Bayesian evidence to identify false positive lag measurements, as well as examine the question of how many AGN present detectable lags in high redshift industrial scale surveys like OzDES and SDSS. Our analysis differs from previous RM studies in six key respects: (i) our inference is robust to the previously under-diagnosed numerical component of aliasing, (ii) we use a consistent methodology for all sources, (iii) uncertainty in the underlying AGN variability is fully marginalised, (iv) lag significance is assessed via Bayesian model comparison rather than heuristic metrics, (v) false-positive rates are quantified by comparison against random-chance recoveries and (vi) we use marginal likelihoods to distinguish between sources where a lag is not detectable in our data and sources that show no evidence of reverberation. Applied to the OzDES sample, we find that previous RM studies are likely to have overestimated the confidence of recovered lags, and we find a stark contrast between a low reverberation percentage for the MgII line (3-28% depending on assumptions) and much higher percentages in the CIV and especially the H$β$ line, which is consistent with 100%. We also present a re-analysed set of lags from the OzDES sample with better quantified reliabilities
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Submitted 2 August, 2026;
originally announced August 2026.
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Stacked Reverberation Mapping of High Redshift Quasars in DESI. I. Feasibility Analysis
Authors:
Rahma Alfarsy,
R. E. A. Canning,
Eva-Maria Mueller,
Jessica Aguilar,
Steven Ahlen,
David Alexander,
Davide Bianchi,
David Brooks,
Peter Clark,
Todd Claybaugh,
Andrei Cuceu,
Tamara Davis,
Axel de la Macorra,
Saisrinivas Dhavala,
Victoria A. Fawcett,
Benjamin Floyd,
Andreu Font-Ribera,
Jaime Forero-Romero,
Enrique Gaztañaga,
Wei-Jian Guo,
Gaston Gutierrez,
Klaus Honscheid,
Richard Joyce,
Stephanie Juneau,
David Kirkby
, et al. (27 additional authors not shown)
Abstract:
The broad line region of quasars has long been probed by reverberation mapping techniques that measure time lags between continuum and broad emission line variations. Stacked reverberation mapping has been proposed as a less observationally expensive alternative to traditional methods. This ensemble approach also reduces biases from small-number statistics. The Dark Energy Spectroscopic Instrument…
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The broad line region of quasars has long been probed by reverberation mapping techniques that measure time lags between continuum and broad emission line variations. Stacked reverberation mapping has been proposed as a less observationally expensive alternative to traditional methods. This ensemble approach also reduces biases from small-number statistics. The Dark Energy Spectroscopic Instrument (DESI) is conducting the most extensive spectroscopic survey of quasars to date. We create mock light curves emulating expected DESI quasar observations at redshifts $1.48<z<5.2$ and luminosities $ 44.68 \leq \log L_{1350} λ/ \mathrm{erg\,s^{-1}} \leq 45.99 $ to test stacked reverberation mapping feasibility using sparse spectroscopic data paired with well-sampled photometric data. The pipeline, using the lag estimation code JAVELIN, successfully recovers the simulated C IV lags within one sigma of the true values using spectroscopic light curves composed of only a few spectral epochs (2-10) with irregular cadences. We investigate how observational factors, including C IV flux error magnitude, number of stacked quasars, and spectral epoch count, affect performance. This work motivates a pathway for future stacked reverberation mapping projects with large scale spectroscopic surveys of quasars having $\geq 2$ spectroscopic observations. Our results suggest an economical alternative for constraining and extending the radius-luminosity relation to higher redshifts and luminosities. Subsequently, this relation can be employed more reliably in single-epoch black hole mass measurements and quasar cosmology in these distant regimes.
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Submitted 23 July, 2026;
originally announced July 2026.
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Fortifying gravitational-wave population inference with normalizing flows
Authors:
Christian Adamcewicz,
Hugh McDougall,
Paul D. Lasky,
Eric Thrane
Abstract:
As the LIGO-Virgo-KAGRA collaboration's (LVK's) gravitational-wave transient catalog grows, we are learning a wealth of information from the population properties of binary black hole mergers. Events in the catalog are represented with posterior samples describing the astrophysical parameters for each event. Population studies combine these samples to measure the distribution of astrophysical para…
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As the LIGO-Virgo-KAGRA collaboration's (LVK's) gravitational-wave transient catalog grows, we are learning a wealth of information from the population properties of binary black hole mergers. Events in the catalog are represented with posterior samples describing the astrophysical parameters for each event. Population studies combine these samples to measure the distribution of astrophysical parameters such as black hole masses and spins. However, the posterior-sample representation of each event is only approximate. We construct a mock population with masses drawn from an astrophysically-motivated distribution with sharp features. Using this, we demonstrate that when $\gtrsim 300$ events are combined, even with each event's posterior represented by $1 \times 10^4 {-} 2 \times 10^4$ samples, the numerical error can become large enough that the resulting population inference is unreliable. We consider two solutions. In the short term, we show that nested samples (already produced by LVK analyses) can be used to more accurately describe each event in population studies. But this will only grant a temporary reprieve until the nested-sample representation becomes inadequate. In the longer term, we propose to represent each event with a normalizing flow. In order to represent each event with sufficient accuracy, each normalizing flow can be used to generate an arbitrarily large number of new posterior samples with a significantly reduced computational cost relative to traditional sampling methods. When compared to nested sampling, our normalizing flows produce posterior draws with a median of $\approx 80\%$ fewer likelihood evaluations per sample, while also providing greater opportunity for parallelization. We believe refinement of normalizing flow architectures and training techniques in future works could further reduce this per-sample cost significantly.
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Submitted 24 July, 2026; v1 submitted 12 June, 2026;
originally announced June 2026.
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OzDES Reverberation Mapping of Active Galactic Nuclei: Final Data Release, Black-Hole Mass Results, & Scaling Relations
Authors:
H. McDougall,
T. M. Davis,
Z. Yu,
P. Martini,
C. Lidman,
U. Malik,
A. Penton,
G. F. Lewis,
B. E. Tucker,
B. J. S. Pope,
S. Allam,
F. Andrade-Oliveira,
J. Asorey,
D. Bacon,
S. Bocquet,
D. Brooks,
A. Carnero Rosell,
D. Carollo,
A. Carr,
J. Carretero,
T. Y. Cheng,
L. N. da Costa,
M. E. da Silva Pereira,
J. De Vicente,
H. T. Diehl
, et al. (31 additional authors not shown)
Abstract:
Over the last decade, the Australian Dark Energy (OzDES) collaboration has used Reverberation Mapping to measure the masses of high redshift supermassive black holes. Here we present the final review and analysis of this OzDES reverberation mapping campaign. These observations use 6-7 years of photometric and spectroscopic observations of 735 Active Galactic Nuclei (AGN) in the redshift range 0.13…
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Over the last decade, the Australian Dark Energy (OzDES) collaboration has used Reverberation Mapping to measure the masses of high redshift supermassive black holes. Here we present the final review and analysis of this OzDES reverberation mapping campaign. These observations use 6-7 years of photometric and spectroscopic observations of 735 Active Galactic Nuclei (AGN) in the redshift range 0.13-3.85 and bolometric luminosity range 44.3 - 47.5 erg/s. Both photometry and spectra are observed in visible wavelengths, allowing for the physical scale of the AGN broad line region to be estimated from reverberations of the H\b{eta}, MgII and CIV emission lines. We successfully use reverberation mapping to constrain the masses of 62 super-massive black holes, and combine with existing data to fit a power law to the lag-luminosity relation for the H\b{eta} and MgII lines with a scatter of ~0.25 dex, the tightest yet identified, fit specifically for consistency with high redshift AGN. We fit a similarly constrained relation for CIV, resolving a tension with the low luminosity literature AGN by accounting for selection effects arising from finite survey length. We also examine the impact of emission line width and luminosity (related to accretion rate) in reducing the scatter of these scaling relationships and find no significant improvement over the lag-only approach for any of the three lines. Using these relations, we further estimate the masses and accretion rates of 246 AGN with single epoch methods. We also use these relations to estimate the relative sizes of the H\b{eta}, MgII and CIV emitting regions. In short, we provide a comprehensive benchmark of high redshift AGN reverberation mapping at the close of this most recent generation of surveys, including light curves, time-delays, and a set of significantly improved radius-luminosity relations for use with high-redshift populations.
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Submitted 24 June, 2026; v1 submitted 30 November, 2025;
originally announced December 2025.
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OzDES Reverberation Mapping Program: CIV lags from six years of data
Authors:
A. Penton,
H. McDougall,
T. M. Davis,
Z. Yu,
U. Malik,
P. Martini,
B. E. Tucker,
C. Lidman,
G. F. Lewis,
R. Sharp,
M. Aguena,
S. Allam,
F. Andrade-Oliveira,
J. Asorey,
D. Bacon,
S. Bocquet,
D. Brooks,
R. Camilleri,
A. Carnero Rosell,
D. Carollo,
A. Carr,
J. Carretero,
T. Y. Cheng,
L. N. da Costa,
M. E. da Silva Pereira
, et al. (30 additional authors not shown)
Abstract:
We present 29 successfully recovered CIV time lags in Active Galactic Nuclei from the complete Dark Energy Survey Reverberation Mapping campaign. The AGN in this sample span a redshift range of 1.9<z<3.5. We successfully measure the velocity dispersion from the CIV spectral linewidth for 25 of these 29 sources, and use these to calculate new high-redshift black hole mass estimates, finding masses…
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We present 29 successfully recovered CIV time lags in Active Galactic Nuclei from the complete Dark Energy Survey Reverberation Mapping campaign. The AGN in this sample span a redshift range of 1.9<z<3.5. We successfully measure the velocity dispersion from the CIV spectral linewidth for 25 of these 29 sources, and use these to calculate new high-redshift black hole mass estimates, finding masses between 0.8 and 1.3 billion solar masses. We also identify a selection effect due to the duration of the survey that can impact the radius-luminosity relation derived from this and other (high-redshift) data. This paper represents the culmination of the OzDES CIV campaign.
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Submitted 15 July, 2026; v1 submitted 30 November, 2025;
originally announced December 2025.
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Helios: A 98-qubit trapped-ion quantum computer
Authors:
Anthony Ransford,
M. S. Allman,
Jake Arkinstall,
J. P. Campora III,
Samuel F. Cooper,
Robert D. Delaney,
Joan M. Dreiling,
Brian Estey,
Caroline Figgatt,
Alex Hall,
Ali A. Husain,
Akhil Isanaka,
Colin J. Kennedy,
Nikhil Kotibhaskar,
Ivaylo S. Madjarov,
Karl Mayer,
Alistair R. Milne,
Annie J. Park,
Adam P. Reed,
Riley Ancona,
Molly P. Andersen,
Pablo Andres-Martinez,
Will Angenent,
Liz Argueta,
Benjamin Arkin
, et al. (161 additional authors not shown)
Abstract:
We report on Quantinuum Helios, a 98-qubit trapped-ion quantum processor based on the quantum charge-coupled device (QCCD) architecture. Helios features $^{137}$Ba$^{+}$ hyperfine qubits, all-to-all connectivity enabled by a rotatable ion storage ring connecting two quantum operation regions by a junction, speed improvements from parallelized operations, and a new software stack with real-time com…
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We report on Quantinuum Helios, a 98-qubit trapped-ion quantum processor based on the quantum charge-coupled device (QCCD) architecture. Helios features $^{137}$Ba$^{+}$ hyperfine qubits, all-to-all connectivity enabled by a rotatable ion storage ring connecting two quantum operation regions by a junction, speed improvements from parallelized operations, and a new software stack with real-time compilation of dynamic programs. Averaged over all operational zones in the system, we achieve average infidelities of $2.5(1)\times10^{-5}$ for single-qubit gates, $7.9(2)\times10^{-4}$ for two-qubit gates, and $4.8(6)\times10^{-4}$ for state preparation and measurement, none of which are fundamentally limited and likely able to be improved. These component infidelities are predictive of system-level performance in both random Clifford circuits and random circuit sampling, the latter demonstrating that Helios operates well beyond the reach of classical simulation and establishes a new frontier of fidelity and complexity for quantum computers.
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Submitted 7 November, 2025;
originally announced November 2025.
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LITMUS: Bayesian Lag Recovery in Reverberation Mapping with Fast Differentiable Models
Authors:
Hugh McDougall,
Tamara M. Davis,
Benjamin J. S. Pope
Abstract:
Reverberation mapping is a technique in which the mass of a Seyfert I galaxy's central supermassive black hole is estimated, along with the system's physical scale, from the timescale at which variations in brightness propagate through the galactic nucleus. This mapping allows for a long baseline of time measurements to extract spatial information beyond the angular resolution of our telescopes, a…
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Reverberation mapping is a technique in which the mass of a Seyfert I galaxy's central supermassive black hole is estimated, along with the system's physical scale, from the timescale at which variations in brightness propagate through the galactic nucleus. This mapping allows for a long baseline of time measurements to extract spatial information beyond the angular resolution of our telescopes, and is the main means of constraining supermassive black hole masses at high redshift. The most recent generation of multi-year reverberation mapping campaigns for large numbers of active galactic nuclei (e.g. OzDES) have had to deal with persistent complications of identifying false positives, such as those arising from aliasing due to seasonal gaps in time-series data. We introduce LITMUS (Lag Inference Through the Mixed Use of Samplers), a modern lag recovery tool built on the "damped random walk" model of quasar variability, built in the autodiff framework JAX. LITMUS is purpose built to handle the multimodal aliasing of seasonal observation windows and provides evidence integrals for model comparison, a more quantified alternative to existing methods of lag validation. LITMUS also offers a flexible modular framework for extending modelling of AGN variability, and includes JAX-enabled implementations of other popular lag recovery methods like nested sampling and the interpolated cross correlation function. We test LITMUS on a number of mock light curves modelled after the OzDES sample and find that it recovers their lags with high precision and a successfully identifies spurious lag recoveries, reducing its false positive rate to drastically outperform the state of the art program JAVELIN. LITMUS's high performance is accomplished by an algorithm for mapping the Bayesian posterior density which both constrains the lag and offers a Bayesian framework for model null hypothesis testing.
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Submitted 24 June, 2026; v1 submitted 14 May, 2025;
originally announced May 2025.
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Unraveling Log4Shell: Analyzing the Impact and Response to the Log4j Vulnerabil
Authors:
John Doll,
Carson McCarthy,
Hannah McDougall,
Suman Bhunia
Abstract:
The realm of technology frequently confronts threats posed by adversaries exploiting loopholes in programs. Among these, the Log4Shell vulnerability in the Log4j library stands out due to its widespread impact. Log4j, a prevalent software library for log recording, is integrated into millions of devices worldwide. The Log4Shell vulnerability facilitates remote code execution with relative ease. It…
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The realm of technology frequently confronts threats posed by adversaries exploiting loopholes in programs. Among these, the Log4Shell vulnerability in the Log4j library stands out due to its widespread impact. Log4j, a prevalent software library for log recording, is integrated into millions of devices worldwide. The Log4Shell vulnerability facilitates remote code execution with relative ease. Its combination with the extensive utilization of Log4j marks it as one of the most dangerous vulnerabilities discovered to date. The severity of this vulnerability, which quickly escalated into a media frenzy, prompted swift action within the industry, thereby mitigating potential extensive damage. This rapid response was crucial, as the consequences could have been significantly more severe if the vulnerability had been exploited by adversaries prior to its public disclosure.
This paper details the discovery of the Log4Shell vulnerability and its potential for exploitation. It examines the vulnerability's impact on various stakeholders, including governments, the Apache Software Foundation (which manages the Log4j library), and companies affected by it. The paper also describes strategies for defending against Log4Shell in several scenarios. While numerous Log4j users acted promptly to safeguard their systems, the vulnerability remains a persistent threat until all vulnerable instances of the library are adequately protected.
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Submitted 29 January, 2025;
originally announced January 2025.